This paper presents an advanced Internet of Things point-of-care bio-fluid analyzer; a LoRa/Bluetooth-enabled electronic reader for biomedical strip-based diagnostics system for personalized monitoring. We undertake test simulations (technology trial without patient subjects) to demonstrate potential of long-range analysis, using a disposable test ‘key’ and companion Android app to form a diagnostic platform suitable for remote point-of-care screening for urinary tract infection (UTI). The 868 MHz LoRaWAN-enabled personalized monitor demonstrated sound potential with UTI test results being correctly diagnosed and transmitted to a remote secure cloud server in every case. Tests ranged over distances of 1.1–6.0 Km with radio path losses from 119–141 dB. All tests conducted were correctly and robustly received at the base station and relayed to the secure server for inspection. The UTI test strips were visually inspected for correct diagnosis based on color change and verified as 100% accurate. Results from testing across a number of regions indicate that such an Internet of Things medical solution is a robust and simple way to deliver next generation community-based smart diagnostics and disease management to best benefit patients and clinical staff alike. This significant step can be applied to any type of home or region, particularly those lacking suitable mobile signals, broadband connections, or even landlines. It brings subscription-free long-range bio-telemetry to healthcare providers and offers savings on regular clinician home visits or frequent clinic visits by the chronically ill. This paper highlights practical hurdles in establishing an Internet of Medical Things network, assisting informed deployment of similar future systems.

An evaluation of a newly CE approved bedside monitoring device used in a general hospital ward is presented. This evaluation has shown that it is feasible to use the system within this environment to provide medical staff with supplementary information on patient health, at more frequent intervals than traditional monitoring methods. The physiological data recorded by the body worn device is wirelessly transmitted to a patient management system for storage and display. Good correlation between heart rate values recorded by hospital staff and those recorded by the automated Vitalsens VS100 system was observed. The system has highlighted clinical information that routine observations alone did not readily identify. This can provide clinicians with a better view of the overall health status of the patient. Such medical issues include those witnessed in this study, namely paroxysmal AF, ectopic beats, increasing heart rates recorded prior to a hypoglycaemic event, general high and low heart rate trends and various instances where clinically relevant ECG data has been captured.

This paper presents the results of a campaign to investigate the empirical characterisation and mathematic modelling of the radio channel for a body-centric LoRaWAN (Long Range Wide Area Network) transceiver for various operating distances across various environments including urban, suburban, and rural. The radio channel for a wearable LoRa transceiver device was explored, as well as anechoic measurements to understand body-shadowing effects. Results indicate that the best fit model for all recorded received signal strength measurements (using the Akaike information criterion to fit) is the Nakagami distribution with mu = 0.52 and Ω = 662.13. Anechoic measurements indicated typical additional effects regarding the orientation of the user with respect to the gateway location. This work highlights LoRaWAN as a credible wearable wireless technology.

Received signal strength measurements and delay statistics are presented for both a stationary and mobile user equipped with a wearable UWB radio transmitter within a hospital environment. The measurements were made for both waist and chest mounted antennas using RF-over-fibre technology to eliminate any spurious electromagnetic scattering effects associated with metallic co-axial cables. The results show that received signal strength values were dependent on whether transmit and receive antennas had line of sight and were also affected by body-shadowing and antenna-body position. For mobile conditions, received signal strength tended to be lognormally distributed with non line of sight links having significantly lower mean values. Excess time delay results for mobile user tests were best described by the Weibull distribution. Overall, the results favoured the chest mounted antenna position, with higher mean signal levels, reduced mean excess delay and less difference between line of sight and non line of sight channels.

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